Instructions to use research-dump/roberta_temp_classifier_bootstrapped with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta_temp_classifier_bootstrapped with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta_temp_classifier_bootstrapped")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta_temp_classifier_bootstrapped") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta_temp_classifier_bootstrapped", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d5ccd4476314cf63b650291c810c142af4d7796afcdf9f2d2e8bfe5e26943d0
- Size of remote file:
- 4.03 kB
- SHA256:
- 3505c95f711b0b133db6aa7b831ddd79df562f5e07767e6e89ca71650d422a5c
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